Speech decoding from EEG signals is a challenging task, where brain activity is modeled to
estimate salient characteristics of acoustic stimuli. We propose FESDE, a novel framework …

This paper describes the auditory EEG challenge, organized as one of the Signal
Processing Grand Challenges at ICASSP 2024. The challenge provides …

Abstract Auditory Attention Decoding (AAD) is a technique that determines the focus of a
listener's attention in complex auditory scenes according to cortical neural responses …

In recent years, speech diffusion models have advanced rapidly. Alongside the widely used
U-Net architecture, transformer-based models such as the Diffusion Transformer (DiT) have …

Decoding speech from brain signals is a challenging research problem that holds significant
importance for studying speech processing in the brain. Although breakthroughs have been …

Brain-computer interfaces (BCI) offer numerous human-centered application possibilities,
particularly affecting people with neurological disorders. Text or speech decoding from brain …

Auditory Attention Decoding (AAD) can help to determine the identity of the attended
speaker during an auditory selective attention task, by analyzing and processing …

The human brain has the ability to selectively focus on a specific auditory stimulus in multi-
speaker scenarios. Recently, it was shown that clues on the target speaker can be extracted …